import torch
import torch.nn as nn
import torch.nn.functional as F


class Q_Network(nn.Module):

    def __init__(self, state_size, action_size, bs, hidden=[128, 128]):
        super(Q_Network, self).__init__()
        self.state_size = 80
        self.action_size = action_size
        self.bs = bs
        self.fc1 = nn.Linear(self.state_size, hidden[0])
        self.fc2 = nn.Linear(hidden[0], hidden[1])
        self.fc3 = nn.Linear(hidden[1], action_size)

    def forward(self, state):
        x = state.reshape(-1, self.state_size)
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x
